Extended Data Fig. 10: RNA-based predictions from CAT improve DNA-based scores.

a, Precision-recall curves comparing the overall prediction performance on non-accessible GTEx tissues using the gene-level FRASER p-values from the CAT, AbSplice-RNA trained on a single CAT and AbSplice-DNA. Each panel shows a different CAT and the number of matching samples in the non-accessible tissues. b, Same as a, but for samples having RNA-seq from both blood and fibroblasts. AbSplice-RNA (all CATs) was trained using RNA-seq data from blood, fibroblasts and lymphocytes. Note that AbSplice-RNA (fibroblasts) gave a similar performance as AbSplice-RNA (all CATs). We did not restrict the samples to the ones also having lymphocytes as this would result in a low number of samples (N = 2,258). c, Model performance for genes not expressed or expressed in the clinically accessible tissue fibroblasts. The cutoff for calling a gene expressed was TPM > 1 (transcript per million). AbSplice-RNA improves for genes expressed in fibroblasts and remains on par with AbSplice-DNA for genes not expressed in fibroblasts.